Application of siemens SMART neuro attenuation correction in brain PET imaging

Siemens SMART neuro attenuation correction (SNAC) is a new type of calculated attenuation correction (CAC) method. This article aimed to evaluate the effect of SNAC on the quantitative analysis of brain positron emission tomography (PET) imaging. Brain PET images of 52 healthy participants after reconstructed by SNAC and CT attenuation correction (CTAC) were analyzed qualitatively by visual analysis, and quantitatively by Scenium software to compare their contrast, signal-to-noise ratio (SNR) as well as the mean standardized uptake value (SUV(mean)) of different brain regions. Compared with CTAC, reconstruction of images by SNAC significantly reduced the SNR by 17.3% (P < .001), but not affected the contrast (P = .440). In addition, the SUV(mean) of different brain regions in images reconstructed by SNAC is increased, but still significantly correlated with that by CTAC (r = 0.988, P < .001), with a coefficient of R(2) = 0.976 in linear regression analysis. Moreover, the mean percent difference of SUV(mean) between images reconstructed with SNAC and CTAC was 8.03% ± 5.38%, varying significantly in the range of −7.56% to 75.31% among 10 different brain regions (F = 35.702, P < .001) and showed greater percent difference in the peripheral brain regions than in the mesial brain regions. Image reconstruction by SNAC has greater effect on quantitative analysis by increasing SUV(mean) of different brain regions to varying degrees, but has little influence on the brain PET image quality. Moreover, it simplifies examination process and reduces radiation dose, which is beneficial to pediatric patients as well as serial scans to monitor therapy.